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首页> 外文期刊>Geophysical Prospecting >Understanding acquisition and processing error in microseismic data: An example from Pouce Coupe Field, Canada
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Understanding acquisition and processing error in microseismic data: An example from Pouce Coupe Field, Canada

机译:了解微地震数据中的采集和处理错误:加拿大Pouce Coupe Field的示例

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A challenge in microseismic monitoring is quantification of survey acquisition and processing errors, and how these errors jointly affect estimated locations. Quantifying acquisition and processing errors and uncertainty has multiple benefits, such as more accurate and precise estimation of locations, anisotropy, moment tensor inversion and, potentially, allowing for detection of 4D reservoir changes. Here, we quantify uncertainty due to acquisition, receiver orientation error, and hodogram analysis. Additionally, we illustrate the effects of signal to noise ratio variances upon event detection. We apply processing steps to a downhole microseismic dataset from Pouce Coupe, Alberta, Canada. We use a probabilistic location approach to identify the optimal bottom well location based upon known source locations. Probability density functions are utilized to quantify uncertainty and propagate it through processing, including in source location inversion to describe the three-dimensional event location likelihood. Event locations are calculated and an amplitude stacking approach is used to reduce the error associated with first break picking and the minimization with modelled travel times. Changes in the early processing steps have allowed for understanding of location uncertainty of the mapped microseismic events.
机译:微地震监测中的挑战是量化调查采集和处理误差,以及这些误差如何共同影响估计位置。量化采集和处理误差以及不确定性具有多重好处,例如更精确地估计位置,各向异性,矩张量反转,并有可能允许检测4D储层变化。在这里,我们对由于采集,接收器方向误差和直方图分析导致的不确定性进行量化。此外,我们说明了事件检测中信噪比方差的影响。我们将处理步骤应用于来自加拿大艾伯塔省Pouce Coupe的井下微地震数据集。我们使用一种概率定位方法,根据已知源位置确定最佳的底部井位。概率密度函数用于量化不确定性并通过处理传播它,包括在源位置反演中描述三维事件位置可能性。计算事件位置,并使用幅度叠加方法来减少与第一次休息挑选相关的误差,并通过建模的行驶时间将其最小化。早期处理步骤中的变化已经允许理解所映射的微地震事件的位置不确定性。

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